Senior AI Engineer: Generative & Agentic Systems

AgentixLake GmbH; Abu Dhabi; On-site; AED 404,000 - 624,000; Full time

Job summary

AgentixLake GmbH in Hamburg seeks an experienced AI engineer to take enterprise AI applications from design to dependable production. You will own evaluations and operational controls for generative AI systems handling customer data and business processes.

Role covers end-to-end design, implementation, and deployment of Python services connecting LLMs to enterprise APIs and tools, with a focus on reliability, monitoring, and cost efficiency.

Qualifications

• Proven production software and LLM applications with architecture deployment and operational quality.
• Strong Python, API design, testing and debugging with containers, Git and CI/CD.
• Hands-on experience with RAG tools, structured outputs, and evaluation beyond prompt experimentation.
• Experience with model services such as Bedrock and Anthropic Claude or similar.
• Ability to explain data access, untrusted inputs and agent permissions in English.

Responsibilities

• Design and implement Python services connecting LLMs to enterprise APIs, data sources, and approved tools.
• Build retrieval-augmented generation systems including document ingestion, indexing, retrieval, reranking, and source attribution.
• Engineer agentic workflows with permissions, state handling, retries, audit trails, and approval gates for consequential actions.
• Develop document intelligence pipelines that produce validated structured outputs for downstream apps and ERP workflows.
• Create evaluation datasets and release criteria; measure answer quality, latency, and operating cost.
• Deploy and operate AI applications in customer-controlled cloud or private environments with monitoring and handover documentation.

Job description

AgentixLake GmbH in Hamburg seeks an experienced AI engineer to take enterprise AI applications from design to dependable production. You will own evaluations and operational controls for generative AI systems handling customer data and business processes.

Role covers end-to-end design, implementation, and deployment of Python services connecting LLMs to enterprise APIs and tools, with a focus on reliability, monitoring, and cost efficiency.